high performance computing on graphics processing units: hgpu.org

Heiko Burau, Renee Widera, Wolfgang Honig, Guido Juckeland, Ale Debus, Thomas Kluge, Ulrich Schramm, Tomas E. Cowan, Roland Sauerbrey, Michael Bussmann

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Tags: CUDA, GPU cluster, nVidia, OpenCL, Particle-in-cell methods, Physics, Plasma physics, Tesla S1070

November 7, 2010 by hgpu

Data-intensive document clustering on GPU clusters

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Computer science, CUDA, Data mining, GPU cluster, nVidia

November 7, 2010 by hgpu

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

Rio Yokota, Jaydeep P. Bardhan, Matthew G. Knepley, L. A. Barba, Tsuyoshi Hamada

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Source codes

Tags: Chemistry, CUDA, GPU cluster, Molecular modeling, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

Exploring the multiple-GPU design space

Dana Schaa, David Kaeli

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce 8800 GTX

November 6, 2010 by hgpu

GAMER with out-of-core computation

Hsi-Yu Schive, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla T10

November 4, 2010 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

Reionization simulations powered by GPUs I: the structure of the Ultraviolet radiation field

General purpose Molecular Dynamics Simulations on GPUs: Issues of Pair Forces and Scaling to large Clusters

Direct N-body simulations of globular clusters: (I) Palomar 14

Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

Parallelizing the QUDA Library for Multi-GPU Calculations in Lattice Quantum Chromodynamics

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU clusters

PIConGPU: A Fully Relativistic Particle-in-Cell Code for a GPU Cluster

Data-intensive document clustering on GPU clusters

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

Exploring the multiple-GPU design space

GAMER with out-of-core computation

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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